Design and Analysis of a Single-Camera Omnistereo Sensor for Quadrotor Micro Aerial Vehicles (MAVs)
This work addresses the need for lightweight 3D sensing in MAVs, though it appears incremental as it builds on existing catadioptric omnistereo methods.
The authors tackled the problem of enabling stereo vision for micro aerial vehicles (MAVs) with low payloads by designing a single-camera omnistereo sensor using hyperboloidal mirrors, achieving practical 3D sensing with analytical solutions for projective geometry and uncertainty estimation.
We describe the design and 3D sensing performance of an omnidirectional stereo-vision system (omnistereo) as applied to Micro Aerial Vehicles (MAVs). The proposed omnistereo model employs a monocular camera that is co-axially aligned with a pair of hyperboloidal mirrors (folded catadioptric configuration). We show that this arrangement is practical for performing stereo-vision when mounted on top of propeller-based MAVs characterized by low payloads. The theoretical single viewpoint (SVP) constraint helps us derive analytical solutions for the sensor's projective geometry and generate SVP-compliant panoramic images to compute 3D information from stereo correspondences (in a truly synchronous fashion). We perform an extensive analysis on various system characteristics such as its size, catadioptric spatial resolution, field-of-view. In addition, we pose a probabilistic model for uncertainty estimation of the depth from triangulation for skew back-projection rays. We expect to motivate the reproducibility of our solution since it can be adapted (optimally) to other catadioptric-based omnistereo vision applications.